Artificial intelligence powered AML compliance
Published 10/2026
Created by Guillermo Casal
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Intermediate | Genre: eLearning | Language: English | Duration: 14 Lectures ( 3h 41m ) | Size: 1.4 GB
From Manual Monitoring to Smart Compliance: Empowering AML Professionals with AI.
What you’ll learn
⚡ • You will understand the main concepts of artificial intelligence, machine learning, advanced analytics, natural language processing and generative models
⚡ how to use AI to monitor regulatory changes and support the development and updating of policies, procedures, risk matrices, and compliance controls.
⚡ • You will learn about AI applications for the assessment of money laundering risk, customer segmentation, scoring, prioritization and continuous updating
⚡ how AI can strengthen KYC, due diligence, beneficial ownership identification, PEP analysis, sanctions, and open sources.
⚡ how to apply AI to transactional monitoring to detect anomalies, unusual patterns, fractionation, circular operations, and reduce false positives
⚡ how to use network analytics, generative AI, and OSINT to uncover relationships, reconstruct financial flows, and support the investigation of suspicious transa
⚡ identify the main risks of using AI in AML, including bias, privacy, explainability, hallucinations, model risk, traceability, and the need for supervision
⚡ • You’ll be able to identify automation opportunities, select use cases, and establish a roadmap for implementing AI sustainably within the compliance program
Requirements
❗ Basic knowledge on Anti Money laundering and compliance
Description
This course presents a practical and current overview of the main applications of artificial intelligence (AI) in the prevention, detection, and investigation of money laundering. It is designed for compliance professionals, AML/CFT-AML, audit, risk, financial investigation, financial intelligence, obliged entities, lawyers, and consultants who want to understand how to responsibly incorporate these technologies into their processes.
The program begins with a fundamental aspect: the use of AI to monitor regulatory changes and support the development and updating of standards, policies, procedures, risk matrices, and internal controls. From there, it addresses the fundamentals of artificial intelligence, machine learning, advanced analytics, natural language processing, and generative models applied to the AML environment.
Participants will learn about applications to improve data quality and integration, assess risks, segment customers, update profiles, strengthen KYC and beneficial ownership identification, and optimize transactional monitoring by detecting anomalies, unusual patterns, and outlier operations, including tools to prioritize alerts and reduce false positives.
The course also delves into the analysis of financial networks and relationships, the reconstruction of fund flows, and the investigation of suspicious transactions. The use of generative AI and OSINT to analyze documents, news, public records, and links between people and companies is studied, as well as new threats related to crypto assets, synthetic identities, deepfakes, and AI-enabled fraud.
An essential component is governance. The risks of bias, privacy, explainability, model risk, hallucinations of generative systems, validation, auditing, traceability and human supervision are analyzed.
Finally, the course provides criteria for identifying automation opportunities, selecting use cases based on risk, impact, and feasibility, conducting pilots, defining indicators, and integrating AI into the existing compliance system.
Upon completion, the participant will be able to identify concrete opportunities to apply AI throughout the AML cycle, understanding both its benefits and its necessary limits and controls.
Who this course is for
⭐ • Compliance officers and professionals responsible for anti-money laundering and terrorist financing prevention programs.
⭐ • AML/AML-CFT specialists and analysts who wish to incorporate artificial intelligence into their work processes
⭐ • Internal auditors and risk professionals interested in assessing the use, controls, and risks associated with AI.
⭐ • Financial investigators and financial intelligence analysts who work with suspicious transactions, documentary information and open sources.
⭐ • Professionals from obliged entities involved in KYC, due diligence, transactional monitoring and risk management
⭐ • Lawyers and consultants who advise organizations on compliance, prevention of money laundering and technological transformation
⭐ • Compliance, risk, technology, or innovation managers who need to evaluate AI automation opportunities
⭐ • Professionals interested in understanding how to apply artificial intelligence to the cycle of prevention and investigation of money laundering.
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